Use of Adaptive Diffusion Filters to Estimate In-Vivo Conductivity Images from B1+ Maps

Computing electrical conductivity or electrical
permittivity maps from the measured B1 maps is a
noise-amplifying process due to the Laplacian
computation involved in solving the underlying
electromagnetic field equations. We applied adaptive
diffusion filters (ADFs) to denoise the B1 maps prior to
the ordinary Laplacian computation based on the
second-order difference equation on three consecutive
neighboring pixels in each direction. Both in the
simulations and in-vivo conductivity imaging experiments
at 3T, we observed significant improvements in the
conductivity image quality computed from the noisy B1
maps acquired by the double angle method (DAM).

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